{"ID":2841357,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.12255","arxiv_id":"2511.12255","title":"Fusionista2.0: Efficiency Retrieval System for Large-Scale Datasets","abstract":"The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video retrieval system optimized for speed and usability. All core modules were re-engineered for efficiency: preprocessing now relies on ffmpeg for fast keyframe extraction, optical character recognition uses Vintern-1B-v3.5 for robust multilingual text recognition, and automatic speech recognition employs faster-whisper for real-time transcription. For question answering, lightweight vision-language models provide quick responses without the heavy cost of large models. Beyond these technical upgrades, Fusionista2.0 introduces a redesigned user interface with improved responsiveness, accessibility, and workflow efficiency, enabling even non-expert users to retrieve relevant content rapidly. Evaluations demonstrate that retrieval time was reduced by up to 75% while accuracy and user satisfaction both increased, confirming Fusionista2.0 as a competitive and user-friendly system for large-scale video search.","short_abstract":"The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video retrieval system optimized for speed and usability. All core modules were re-engineered for efficiency: preprocessing now relies on ffmpeg for...","url_abs":"https://arxiv.org/abs/2511.12255","url_pdf":"https://arxiv.org/pdf/2511.12255v2","authors":"[\"Huy M. Le\",\"Dat Tien Nguyen\",\"Phuc Binh Nguyen\",\"Gia Bao Le Tran\",\"Phu Truong Thien\",\"Cuong Dinh\",\"Minh Nguyen\",\"Nga Nguyen\",\"Thuy T. N. Nguyen\",\"Tan Nhat Nguyen\",\"Binh T. Nguyen\"]","published":"2025-11-15T15:23:44Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Language Model\"]","has_code":false}